Create app.py

app.py

@@ -0,0 +1,34 @@
+import gradio as gr
+from PIL import Image
+from transformers import pipeline
+
+
+classifier = pipeline("image-classification", model="Docty/mango-samu")
+
+def classify_image(img):
+    if not isinstance(img, Image.Image):
+        img = Image.fromarray(img)
+    results = classifier(img)
+    return {res["label"]: float(res["score"]) for res in results}
+
+
+theme = gr.themes.Soft(
+    primary_hue="blue",
+    secondary_hue="lime",
+    neutral_hue="slate"
+)
+
+
+with gr.Blocks(theme=theme) as demo:
+    gr.Markdown("## Mango Image Classifier")
+    gr.Markdown("Upload an image of a mango to classify it using a fine-tuned model.")
+
+    with gr.Row():
+        image_input = gr.Image(type="pil", label="Upload Mango Image")
+        label_output = gr.Label(num_top_classes=3, label="Predictions")
+
+    classify_btn = gr.Button("Classify Image", variant="primary")
+
+    classify_btn.click(fn=classify_image, inputs=image_input, outputs=label_output)
+
+demo.launch(share=True)